• Title/Summary/Keyword: named data

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Transformations and Their Analysis from a RGBD Image to Elemental Image Array for 3D Integral Imaging and Coding

  • Yoo, Hoon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.5
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    • pp.2273-2286
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    • 2018
  • This paper describes transformations between elemental image arrays and a RGBD image for three-dimensional integral imaging and transmitting systems. Two transformations are introduced and analyzed in the proposed method. Normally, a RGBD image is utilized in efficient 3D data transmission although 3D imaging and display is restricted. Thus, a pixel-to-pixel mapping is required to obtain an elemental image array from a RGBD image. However, transformations and their analysis have little attention in computational integral imaging and transmission. Thus, in this paper, we introduce two different mapping methods that are called as the forward and backward mapping methods. Also, two mappings are analyzed and compared in terms of complexity and visual quality. In addition, a special condition, named as the hole-free condition in this paper, is proposed to understand the methods analytically. To verify our analysis, we carry out experiments for test images and the results indicate that the proposed methods and their analysis work in terms of the computational cost and visual quality.

A Design of Content-based Metric Learning Model for HR Matching (인재매칭을 위한 내용기반 척도학습모형의 설계)

  • Song, Hee Seok
    • Journal of Information Technology Applications and Management
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    • v.27 no.6
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    • pp.141-151
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    • 2020
  • The job mismatch between job seekers and SMEs is becoming more and more intensifying with the serious difficulties in youth employment. In this study, a bi-directional content-based metric learning model is proposed to recommend suitable jobs for job seekers and suitable job seekers for SMEs, respectively. The proposed model not only enables bi-directional recommendation, but also enables HR matching without relearning for new job seekers and new job offers. As a result of the experiment, the proposed model showed superior performance in terms of precision, recall, and f1 than the existing collaborative filtering model named NCF+GMF. The proposed model is also confirmed that it is an evolutionary model that improves performance as training data increases.

Study on Establishment of DB for Processing Properties of Food Raw Materials and Website Operation (식품자원의 가공적성 연구 결과 DB 구축 및 웹사이트 운영 연구)

  • Hwang, Sin-hee
    • Food Science and Industry
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    • v.49 no.2
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    • pp.78-82
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    • 2016
  • DB Integration website(tentatively named Food Processing Aptitude Information Center, FPAIC) has been designed through a "high-value products development project(2013)". Basically, the project aims to secure connections between food raw materials and processing industry, a variety of information sources, and users's convenience. It also aims to build the industry-university-based mutual growth in the food industry through sharing of processing suitability and material research on food raw materials. FPAIC consists of raw material story, information of sample characteristics, food processing study, preceding research data, food industry trends, and understanding of food processing. The major database of research on Food Processing is provided on information of sample characteristics, and food processing study. Currently the web site has 36 raw material stories, 380 information on sample characteristics and food processing studies, 1,600 preceding research data about 31 food raw materials. The web site also provides information on 70 useful web sites, as well as 77 food industry trends, 27 basic information about food processing.

Feature selection-based Risk Prediction for Hypertension in Korean men (한국 남성의 고혈압에 대한 특징 선택 기반 위험 예측)

  • Dashdondov, Khongorzul;Kim, Mi-Hye
    • Proceedings of the Korea Information Processing Society Conference
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    • 2021.05a
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    • pp.323-325
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    • 2021
  • In this article, we have improved the prediction of hypertension detection using the feature selection method for the Korean national health data named by the KNHANES database. The study identified a variety of risk factors associated with chronic hypertension. The paper is divided into two modules. The first of these is a data pre-processing step that uses a factor analysis (FA) based feature selection method from the dataset. The next module applies a predictive analysis step to detect and predict hypertension risk prediction. In this study, we compare the mean standard error (MSE), F1-score, and area under the ROC curve (AUC) for each classification model. The test results show that the proposed FIFA-OE-NB algorithm has an MSE, F1-score, and AUC outcomes 0.259, 0.460, and 64.70%, respectively. These results demonstrate that the proposed FIFA-OE method outperforms other models for hypertension risk predictions.

High-resolution CMB bispectrum estimator for future surveys

  • Sohn, Wuhyun
    • The Bulletin of The Korean Astronomical Society
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    • v.46 no.2
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    • pp.44.1-44.1
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    • 2021
  • The Cosmic Microwave Background (CMB) contains a wealth of information about the perturbations in the early universe. Its bispectrum, the Fourier counterpart of three-point correlation functions, is a direct probe of primordial non-Gaussianity predicted by many physically well motivated inflation models. Motivated by the substantial improvement in sensitivity expected from future CMB surveys, we developed a novel bispectrum estimator capable of handling such high-resolution data. Our code, named CMB-BEst, utilises a set of separable basis functions to constrain a wide variety of models simultaneously. Flexibility in the choice of basis enables targeted analysis on highly oscillatory inflation models, which are previously unconstrained due to the numerical and computational challenges involved. We present the results of our thorough validation tests, both internal and against conventional approaches. We provide a proof-of-concept example with Planck satellite data and sketch out the road ahead.

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2Q-CFP: A Client Cache Management Scheme for Broadcast-based Information Systems (2Q-CFP: 방송에 기초한 정보 시스템을 위한 클라이언트 캐쉬 관리 기법)

  • 권혁민
    • Journal of KIISE:Databases
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    • v.30 no.6
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    • pp.561-572
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    • 2003
  • Broadcast-based data delivery has attracted a lot of attention as an efficient way of disseminating data to very large client populations. The main motivation of broadcast-based information systems (BBISs) is that the number of clients that they serve can grow arbitrarily large without any effect on their performance. The performance of BBISs depends mainly on client caching strategies and on data broadcast scheduling mechanisms. This paper addresses the former issue and proposes a new client cache management scheme, named 2Q-CFP, that is suitable to BBISs. This paper also evaluates the performance of 2Q-CFP on the basis of a simulation model. The performance results indicate that 2Q-CFP scheme shows superior performances over GRAY, LRU and CF in the average response time.

Automated Test Data Generation for Testing Programs with Multi-level Stack-directed Pointers (다단계 스택 지향 포인터가 있는 프로그램 테스트를 위한 테스트 데이터 자동 생성)

  • Chung, In-Sang
    • The KIPS Transactions:PartD
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    • v.17D no.4
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    • pp.297-310
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    • 2010
  • Recently, a new testing technique called concolic testing receives lots of attention. Concolic testing generates test data by combining concrete program execution and symbolic execution to achieve high test coverage. CREST is a representative open-source test tool implementing concolic testing. Currently, however, CREST only deals with integer type as input. This paper presents a new rule for automated test data generation in presence of inputs of pointer type. The rules effectively handles multi-level stack-directed pointers that are mainly used in C programs. In addition, we describe a tool named vCREST implementing the proposed rules together with the results of applying the tool to some C programs.

Density Aware Energy Efficient Clustering Protocol for Normally Distributed Sensor Networks

  • Su, Xin;Choi, Dong-Min;Moh, Sang-Man;Chung, Il-Yong
    • Journal of Korea Multimedia Society
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    • v.13 no.6
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    • pp.911-923
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    • 2010
  • In wireless sensor networks (WSNs), cluster based data routing protocols have the advantages of reducing energy consumption and link maintenance cost. Unfortunately, most of clustering protocols have been designed for uniformly distributed sensor networks. However, some urgent situations do not allow thousands of sensor nodes being deployed uniformly. For example, air vehicles or balloons may take the responsibility for deploying sensor nodes hence leading a normally distributed topology. In order to improve energy efficiency in such sensor networks, in this paper, we propose a new cluster formation algorithm named DAEEC (Density Aware Energy-Efficient Clustering). In this algorithm, we define two kinds of clusters: Low Density (LD) clusters and High Density (HD) clusters. They are determined by the number of nodes participated in one cluster. During the data routing period, the HD clusters help the neighbor LD clusters to forward the sensed data to the central base station. Thus, DAEEC can distribute the energy dissipation evenly among all sensor nodes by considering the deployment density to improve network lifetime and average energy savings. Moreover, because the HD clusters are densely deployed they can work in a manner of our former algorithm EEVAR (Energy Efficient Variable Area Routing Protocol) to save energy. According to the performance analysis result, DAEEC outperforms the conventional data routing schemes in terms of energy consumption and network lifetime.

STUDY ON 3-D VIRTUAL REALITY FOR STEREOSCOPIC VISUALIZATION ON THE WEB (웹 환경에서의 입체적 가시화를 위한 3-D 가상현실 기법의 적용)

  • Lee, J.H.;Park, Y.C.;Kim, J.H.;Kim, B.S.
    • Journal of computational fluids engineering
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    • v.16 no.1
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    • pp.30-35
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    • 2011
  • In this paper, our effort to apply 3-D Virtual Reality system for stereoscopic visualization of mesh data on the web is briefly described. This study is an extension of our previous and on-going research efforts to develop an automatic grid generation program specialized for wing mesh, named as eGWing. The program is developed by using JAVA programming language, and it can be used either as an application program on a local computer or as an applet in the network environment. In this research advancing layer method(ALM) augmented by elliptic smoothing method is used for the structured grid generation. And to achieve a stereoscopic viewing capability, two graphic windows are used to render its own viewing image for the left and right eye respectively. These two windows are merged into one image using 3D monitor and the viewers can see the mesh data visualization results with stereoscopic depth effects by using polarizing glasses. In this paper three dimensional mesh data visualization with stereoscopic technique combined with 3D monitor is demonstrated, and the current achievement would be a good start-up for further development of low-cost high-quality stereoscopic mesh data visualization system which can be shared by many users through the web.

Generation and Protection of Efficient Watermark Signals and Image Quality Preservation in Transmission Channel Using Turbo Coding (효과적인 워터마크 신호의 생성과 보호 및 터보코딩을 이용한 전송채널상에서의 화질 보존)

  • Cho, Dong-Uk;Bae, Young-Lae
    • The KIPS Transactions:PartB
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    • v.9B no.1
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    • pp.91-98
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    • 2002
  • In this paper, an implementation method of the efficient image transmission stage using watermarking and channel ceding is proposed. Usually, image communication system consists of both a transmitter part and a receiver part. The transmitter part takes charge of copyright protection of the generated image data, and image coding and compression that can deal with channel noises when transmitting. In the transmitter part, we propose a channel coding method which protects both the watermark signal and the original signal for protecting the copyright of image data and solving channel noises when transmitting. Firstly, copyright protection of image data is conducted. For this, image structure analysis is performed, and both the improvement of image quality and the generation of the watermark signal are made. Then, the histogram is constructed and the watermark signals are selected from this. At this stage, by embedding of the coefficients of curve fittness into the lower 4 bits of the image data pixels, image quality degradation due to the embedding of watermark signals are prevented. Finally, turbo coding, which has the most efficient error correction capability in error correction codes, has been conducted to protect signals of watermark and preserved original image quality against noises on the transmission channel. Particularly, a new interleaving method named "semi random inter]easer" has been proposed.